Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
PDF files have become ubiquitous in our multi-platform world. This convenient file format makes it possible to view and share documents across various devices using various operating systems and ...
Radiopharmaceutical therapy (RPT) offers molecular-targeted treatment strategies and presents an ideal model for advancing ...
Abstract: In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters.
Abstract: Convolution and self-attention are two powerful techniques for multisource remote sensing (RS) data fusion that have been widely adopted in Earth observation tasks. However, convolutional ...
@inproceedings{su2020dgc, title={Dynamic Group Convolution for Accelerating Convolutional Neural Networks}, author={Su, Zhuo and Fang, Linpu and Kang, Wenxiong and Hu, Dewen and Pietik{\"a}inen, Matti ...
This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph Convolution (AdaptConv) is a point cloud convolution operator presented in our ICCV2021 paper. If you ...
A research team has developed a new model, PlantIF, that addresses one of the most pressing challenges in agriculture: the accurate and timely ...
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